R Notebook

All cancer cells UMAP

acchigh=read.delim("../data/oncotarget-05-12528-s001_acchigh.txt",skip=0,header=F,sep="\t",stringsAsFactors=F)
acchigh_s=apply(acc_all_cells@assays$RNA@scale.data[intersect(acchigh$V1,acc_all_cells@assays$RNA@var.features),],2,mean)
acchigh_s[acchigh_s < -0.5] = -0.5
acchigh_s[acchigh_s > 0.5] = 0.5
acc_all_cells=AddMetaData(acc_all_cells,acchigh_s,"kaye_acc_score")

CAF markers

FeaturePlot(acc_all_cells, c("COL3A1","COL1A2") ,cols = c("blue","yellow"))

Endothelian markers

FeaturePlot(acc_all_cells, c("VWF","PECAM1") ,cols = c("blue","yellow"))

WBC markers

FeaturePlot(acc_all_cells, c("CD79A","PTPRC") ,cols = c("blue","yellow"))

ACC markers

FeaturePlot(acc_all_cells, c("kaye_acc_score","MYB") ,cols = c("blue","yellow"))

3.Cell types in ACC1

3. UMAP of luminal_over_myo

only cancer cells:

You may also use this plot:

lum_or_myo = FetchData(object = acc_cancer_cells,vars = "luminal_over_myo")
lum_or_myo$luminal_over_myo[lum_or_myo$luminal_over_myo>=1] = "Lum"
lum_or_myo$luminal_over_myo[lum_or_myo$luminal_over_myo<= (-1)] = "Myo"
lum_or_myo$luminal_over_myo[lum_or_myo$luminal_over_myo> (-1) & lum_or_myo$luminal_over_myo<1] = "unassigned"
acc_cancer_cells <- AddMetaData(object = acc_cancer_cells, metadata = lum_or_myo, col.name = "lum_or_myo")

lum_or_myo_by_patient = FetchData(object = acc_cancer_cells,vars = c("lum_or_myo","patient.ident"))


lum_or_myo_by_patient %>% 
  dplyr::count(patient.ident, lum_or_myo) %>% 
  dplyr::add_count(patient.ident, wt = n, name = "overall") %>% 
  mutate(proportion = n / overall) 

NA

lum_or_myo_by_patient = lum_or_myo_by_patient %>% 
  dplyr::count(patient.ident, lum_or_myo) %>% 
  dplyr::add_count(patient.ident, wt = n, name = "overall") %>% 
  mutate(proportion = n / overall) %>% filter(lum_or_myo == "Myo")

ggplot(data=lum_or_myo_by_patient, aes(x=patient.ident, y=proportion)) +
  geom_bar(stat="identity", fill="steelblue")+
  theme_minimal() +ylab("Myo cells %")

4. UMAPS

# acc1_cancer_cells = subset(x = acc_cancer_cells,subset = patient.ident == "ACC1")
# acc1_cancer_cells <- FindVariableFeatures(acc1_cancer_cells, selection.method = "vst", nfeatures = 15000)
# acc1_cancer_cells <- ScaleData(acc1_cancer_cells, vars.to.regress = c("percent.mt","nCount_RNA"))
# acc1_cancer_cells <- RunPCA(acc1_cancer_cells, features = VariableFeatures(object = acc_cancer_cells))
# acc1_cancer_cells <- FindNeighbors(acc1_cancer_cells, dims = 1:10)
# acc1_cancer_cells <- FindClusters(acc1_cancer_cells, resolution = 1)
# acc1_cancer_cells <- RunUMAP(acc1_cancer_cells, dims = 1:10)
# saveRDS(object = acc1_cancer_cells,file = "../Data/acc1_cancer_cells.RDS")
acc1_cancer_cells = readRDS(file = "../Data/acc1_cancer_cells.RDS")
DimPlot(object = acc1_cancer_cells,reduction = "umap")

6. HPV+ cells UMAP

Only HMSC cancer cells:

CNV

CNV for ACC1:

acc1_annotation  = as.data.frame(acc1_all_cells@meta.data[,"seurat_clusters",drop = F])
acc1_annotation = acc1_annotation %>% rownames_to_column("orig.ident") 
acc1_annotation = acc1_annotation %>% mutate(orig.ident = gsub(x = acc1_annotation$orig.ident,pattern = "\\.", replacement = "-") %>% 
  gsub(pattern = "_", replacement = "-"))
  


write.table(acc1_annotation, "../Data/CNV/acc1_annotation.txt", append = FALSE, 
            sep = "\t", dec = ".",row.names = FALSE, col.names = F)

infercnv_obj = CreateInfercnvObject(raw_counts_matrix="../Data/CNV/all.4icnv.txt", 
                                    annotations_file="../Data/CNV/acc1_annotation.txt",
                                    delim="\t",gene_order_file="../Data/CNV/gencode_v19_gene_pos.txt"
                                    ,ref_group_names=c("0", "6", "7", "8", "9")) #groups of normal cells

plot = FeaturePlot(acc1_all_cells, c("VWF") ,cols = c("blue","yellow"))

HoverLocator(plot = plot, information = FetchData(acc_all_cells, vars = c("VWF", "PECAM1","cell.type")))

Warning: the condition has length > 1 and only the first element will be usedWarning: the condition has length > 1 and only the first element will be usedWarning: `error_y.color` does not currently support multiple values.Warning: `error_x.color` does not currently support multiple values.Warning: `line.color` does not currently support multiple values.Warning: The titlefont attribute is deprecated. Use title = list(font = ...) instead.Warning: the condition has length > 1 and only the first element will be usedWarning: the condition has length > 1 and only the first element will be usedWarning: `error_y.color` does not currently support multiple values.Warning: `error_x.color` does not currently support multiple values.Warning: `line.color` does not currently support multiple values.Warning: The titlefont attribute is deprecated. Use title = list(font = ...) instead.

plot = FeaturePlot(acc1_all_cells, c("PECAM1") ,cols = c("blue","yellow"))

HoverLocator(plot = plot, information = FetchData(acc_all_cells, vars = c("VWF", "PECAM1","cell.type")))

Warning: the condition has length > 1 and only the first element will be usedWarning: the condition has length > 1 and only the first element will be usedWarning: `error_y.color` does not currently support multiple values.Warning: `error_x.color` does not currently support multiple values.Warning: `line.color` does not currently support multiple values.Warning: The titlefont attribute is deprecated. Use title = list(font = ...) instead.Warning: the condition has length > 1 and only the first element will be usedWarning: the condition has length > 1 and only the first element will be usedWarning: `error_y.color` does not currently support multiple values.Warning: `error_x.color` does not currently support multiple values.Warning: `line.color` does not currently support multiple values.Warning: The titlefont attribute is deprecated. Use title = list(font = ...) instead.

plot = FeaturePlot(acc1_all_cells, c("COL3A1") ,cols = c("blue","yellow"))

HoverLocator(plot = plot, information = FetchData(acc1_all_cells, vars = c("COL3A1", "COL1A2","cell.type")))

Warning: the condition has length > 1 and only the first element will be usedWarning: the condition has length > 1 and only the first element will be usedWarning: `error_y.color` does not currently support multiple values.Warning: `error_x.color` does not currently support multiple values.Warning: `line.color` does not currently support multiple values.Warning: The titlefont attribute is deprecated. Use title = list(font = ...) instead.Warning: the condition has length > 1 and only the first element will be usedWarning: the condition has length > 1 and only the first element will be usedWarning: `error_y.color` does not currently support multiple values.Warning: `error_x.color` does not currently support multiple values.Warning: `line.color` does not currently support multiple values.Warning: The titlefont attribute is deprecated. Use title = list(font = ...) instead.

plot = FeaturePlot(acc1_all_cells, c("COL1A2") ,cols = c("blue","yellow"))

HoverLocator(plot = plot, information = FetchData(acc1_all_cells, vars = c("COL3A1", "COL1A2","cell.type")))

Warning: the condition has length > 1 and only the first element will be usedWarning: the condition has length > 1 and only the first element will be usedWarning: `error_y.color` does not currently support multiple values.Warning: `error_x.color` does not currently support multiple values.Warning: `line.color` does not currently support multiple values.Warning: The titlefont attribute is deprecated. Use title = list(font = ...) instead.Warning: the condition has length > 1 and only the first element will be usedWarning: the condition has length > 1 and only the first element will be usedWarning: `error_y.color` does not currently support multiple values.Warning: `error_x.color` does not currently support multiple values.Warning: `line.color` does not currently support multiple values.Warning: The titlefont attribute is deprecated. Use title = list(font = ...) instead.

DimPlot(object = acc_all_cells, reduction = "umap", pt.size = 1,cells.highlight= selected_group,
        group.by = "patient.ident", label = TRUE) +
  scale_color_manual(labels = c("unselected", "ACC1"), values = c("grey", "red"))

Scale for 'colour' is already present. Adding another scale for 'colour', which will replace the existing scale.

acc_all_cells = SetIdent(object = acc_all_cells,value = "patient.ident")
selected_group <- WhichCells(acc_all_cells, idents = "ACC1")

acc1_plot = DimPlot(object = acc_all_cells, reduction = "umap", pt.size = 1,cells.highlight= selected_group,
        group.by = "patient.ident", label = TRUE) +
  scale_color_manual(labels = c("unselected", "ACC1"), values = c("grey", "red"))

Scale for 'colour' is already present. Adding another scale for 'colour', which will replace the existing scale.

HoverLocator(plot = acc1_plot, information = FetchData(acc1_all_cells, vars = c("cell.type")))

Warning: The titlefont attribute is deprecated. Use title = list(font = ...) instead.Warning: The titlefont attribute is deprecated. Use title = list(font = ...) instead.

FeaturePlot(object = acc1_cancer_cells,features = c("KIT","CLDN3","ANXA8","EHF","ELF5","KRT7","CLDN4","LCN2","LGALS3","WFDC2","ATP1B1","CD24")
            ,slot = "scale.data")

FeaturePlot(object = acc1_cancer_cells,features = c("TP63","TP73","CDH3","KRT14","KRT5","ACTA2","CDH11","TAGLN","MYLK","DKK3","SPARC","TRIM29")
            ,slot = "scale.data")

correlation of lum/myp markers

lum_markers  = FetchData(object = acc1_cancer_cells, vars = 
                 c("KIT","CLDN3","ANXA8","EHF","ELF5","KRT7","CLDN4","LCN2","LGALS3","WFDC2","ATP1B1","CD24"))
lum_cor = cor(lum_markers)
pheatmap(lum_cor)

myo_markers  = FetchData(object = acc1_cancer_cells, vars = 
                 c("TP63","TP73","CDH3","KRT14","KRT5","ACTA2","CDH11","TAGLN","MYLK","DKK3","SPARC","TRIM29"))
myo_cor = cor(myo_markers)
pheatmap(myo_cor)

myo_proteins = FetchData(object = acc1_cancer_cells,vars = c("CNN1"))
myo_proteins_cor = cor(myo_markers,myo_proteins)
pheatmap(myo_proteins_cor,cluster_cols = F, cluster_rows = F,display_numbers = T)

a = colnames(acc_all_cells) %>% as.data.frame()